Multicenter Study of Acetaminophen Hepatotoxicity Reveals the Importance of Biological Endpoints in Genomic Analyses
Author(s) -
Richard P. Beyer,
Rebecca C. Fry,
Michael Lasarev,
Lisa A. McConnachie,
Lisiane B. Meira,
Valerie S. Palmer,
Christine L. Powell,
Pamela K. Ross,
Theo K. Bammler,
Blair U. Bradford,
Alex B. Cranson,
Michael L. Cunningham,
Rickie D. Fannin,
Gregory Higgins,
Patrick Hurban,
Robert J. Kayton,
Kathleen F. Kerr,
Oksana Kosyk,
Edward K. Lobenhofer,
Stella O. Sieber,
Portia A. Vliet,
Brenda K. Weis,
Russel D. Wolfinger,
Courtney G. Woods,
Jonathan H. Freedman,
Elwood Linney,
William K. Kaufmann,
Terrance J. Kavanagh,
Richard S. Paules,
Ivan Rusyn,
Leona D. Samson,
Peter S. Spencer,
William A. Suk,
Raymond Tennant,
Helmut Zarbl
Publication year - 2007
Publication title -
toxicological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.352
H-Index - 183
eISSN - 1096-6080
pISSN - 1096-0929
DOI - 10.1093/toxsci/kfm150
Subject(s) - toxicogenomics , computational biology , acetaminophen , gene expression profiling , in silico , dna microarray , gene expression , biology , microarray analysis techniques , microarray , bioinformatics , gene , pharmacology , genetics
Gene expression profiling is a widely used technique with data from the majority of published microarray studies being publicly available. These data are being used for meta-analyses and in silico discovery; however, the comparability of toxicogenomic data generated in multiple laboratories has not been critically evaluated. Using the power of prospective multilaboratory investigations, seven centers individually conducted a common toxicogenomics experiment designed to advance understanding of molecular pathways perturbed in liver by an acute toxic dose of N-acetyl-p-aminophenol (APAP) and to uncover reproducible genomic signatures of APAP-induced toxicity. The nonhepatotoxic APAP isomer N-acetyl-m-aminophenol was used to identify gene expression changes unique to APAP. Our data show that c-Myc is induced by APAP and that c-Myc-centered interactomes are the most significant networks of proteins associated with liver injury. Furthermore, sources of error and data variability among Centers and methods to accommodate this variability were identified by coupling gene expression with extensive toxicological evaluation of the toxic responses. We show that phenotypic anchoring of gene expression data is required for biologically meaningful analysis of toxicogenomic experiments.
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